首页>
外国专利>
METHOD AND SYSTEM FOR HIERARCHICAL TIME-SERIES CLUSTERING WITH AUTO ENCODED COMPACT SEQUENCE (AECS)
METHOD AND SYSTEM FOR HIERARCHICAL TIME-SERIES CLUSTERING WITH AUTO ENCODED COMPACT SEQUENCE (AECS)
展开▼
机译:具有自动编码紧凑序列(AEC)的分层时间级聚类的方法和系统
展开▼
页面导航
摘要
著录项
相似文献
摘要
Conventional hierarchical time-series clustering is highly time consuming process as time-series are characteristically lengthy. Moreover, finding right similarity measure providing best possible hierarchical cluster is critical to derive accurate inferences from the hierarchical clusters. Method and system for Auto Encoded Compact Sequences (AECS) based hierarchical time-series clustering that enables compact latent representation of time-series using an undercomplete multilayered Seq2Seq LSTM auto encoder followed by generating of HCs using multiple similarity measures is disclosed. Further, provided is a mechanism to select the best HC among the multiple HCs on-the-fly, based on an internal clustering performance measure of Modified Hubert statistic τ. Thus, the method provides time efficient and low computational cost approach for hierarchical clustering for both on univariate and multivariate time-series. AECS approach provides a constant length sequence across diverse length series and hence provides a generalized approach.
展开▼